In the operation of a copier or printer, particularly color machines, it is highly desirable to have means for variably processing and enhancing text, graphical and pictorial image quality. A typical workflow in a production publishing environment involves the following steps: scanning the hardcopy originals, outputting the scanned image data, and printing the image data through a DFE (Digital Front End) to a printer. The quality of the printed images is limited to the standard processing features and capabilities of the DFE. Particularly, in the case of single or multi-pass color printers, it is highly desirable that an image processing system be employed to reduce imaging problems caused by rendering systems which may not be well suited to each type of image.
Auto-segmentation techniques are known which can select the most appropriate method to render the various object types, (e.g., black and white or color images, text, etc.) present in an image. Such techniques permit an image to be divided into segments, which correspond to structural aspects of the image, and may be used to distinguish various objects of interest within the entire image on a page, and allow different printing properties or methods to be applied to the different document image segments by the DFE.
Specified regions of an image page are separated into classes, such as the typical text, graphics and pictures. Scanned or computer generated electronic document images may be rendered according to various colorization, contrast and/or halftoning techniques, for example. Some rendering techniques are more suitable for printing text regions, while others are more suitable for printing graphics or picture (bitmap) regions. The quality of the printed image can be efficiently improved by first separating all the regions in a document image that need to be evaluated for differential rendering, and then classifying these regions according to the desired rendering techniques. Automatic processing of document images is performed by classifying various regions in a document image into logically separate classes. These classes may be text, graphics and pictures. The image segmentation stage separates an input image into regions or objects. Output of the segmentation stage contains region labels at each pixel in the input image.
Currently, auto-segmentation software applications, for example, ELAN ELP™ from ELAN GMK, are only capable of adding index information (or metadata) after the image data has been exported from a scanner and saved to file.
The inventors have recognized that, if the DFE processing step had more information about each pixel in the image, then more intelligent processing could be applied to improve the overall quality of the output image. The Xerox® FreeFlow Scanner 665™ scanner, for example, produces per pixel information for its own internal use when processing images inside the scanner's hardware/firmware image processing path (e.g., in Automatic Mode). However, this information is presently not exported from the scanner.
Thus, the inventors have recognized that it would be desirable to export metadata associated with the image data from the image capture device to enable more intelligent post-scan processing of the images.